… relative
to the gene, not absolute like it currently is.
Default mean = 1.0
Default std = 0.0333
This means that the values will be multiplied by 1.0 with a std of 0.0333. In
other words, 68% of the time, the multiplier will be within +/- 0.999 (10%) of
the gene value.

…anGradient
The following four mutators are new:
G1DListMutatorRealGaussianGradient
G1DListMutatorIntegerGaussianGradient
G2DListMutatorRealGaussianGradient
G2DListMutatorIntegerGaussianGradient
The main difference between Gaussian and GaussianGradient is that
GaussianGradient uses a multiplicative modification rather than an additive.
GaussianGradient's mu and sigma are absolute, not relative. So if the default
values of mu=2 and std=10 (why not mu=0?) are used, the random gaussian number
is a flat number around 2. If we're working on a huge range, like say 0-100000,
this is a very small drift.
GaussianGradient uses mu=1.0 and std=0.1 to generate a number around 1.0. This
is then *multiplied* by the gene to provide subtle drift regardless of how
large the range is.
2 new constants added, Mu and Sigma for the GaussianGradient routines.